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The Learning Network

Insight: Common Generative AI Misconceptions and How to Demystify Them

Owing to the accelerated advancement in the field of generative AI technologies, it’s important to address misconceptions about what generative AI tools can and cannot do in order to maximize the benefits and minimize potential harms. In this “Ask me Anything” session, Amanda demystifies some of the most commonly held misconceptions about generative AI via discussions of real-world use cases. While responding to specific questions, Amanda highlights areas in which generative AI seems to thrive, while she also identifies notable shortcomings of the technology by drawing from her diverse and extensive experience as a digital transformation expert and a sought-after advisor to leading organizations in artificial intelligence and machine learning technologies.

Insight: Integrating Generative AI Within Organizational Systems Comes With Challenges. Here Is Why Businesses Should Still Invest In This Space, Now More Than Ever

Following the abrupt uptick of generative AI innovation in the past couple of years, organizations have ramped up research and development efforts to meaningfully explore the value of integrating generative AI into organizational systems, with a particular interest in achieving operational hyper-efficiency. This effort requires a deep understanding of the steps towards operationalizing generative AI—from development to adoption to deployment—involving benefits and risks that must be carefully considered to augment performance and financial gains. 

Insight: Here is What the World’s Leading Executives Have to Say About the Emerging Dual Space of Digital and Sustainable Economy

The digital and sustainability paths, previously considered to be parallel, are now highly intersecting and reinforcing each other, pointing towards a symbiotic relationship between technological advancement and environmental values. Showcasing this relationship, digital technologies are expected to contribute more than one-fifth, and up to one-third, of the GHG emissions reduction required by the Paris Agreement by 2030, illustrating their importance to sustainability transformation. As such, it’s important to understand the main drivers of this shift because of the implications this shift has on the global business landscape, including the demand for businesses to prioritize integrating digital innovation with sustainable practices. With the eco-digital economy including benefits that extend well beyond improvement in core business activities, it’s imperative for leaders to have a vision for digital transformation at their organizations going forward with a focus on harnessing the opportunities created by the emerging eco-digital economy including digital strategy, cybersecurity, sustainability, and more. 

Insight: Concepts, Applications, and Opportunities in the New Age of AI Product Management

Understanding AI product management has become more crucial than ever, particularly in light of recent advancements in the spaces of AI and Machine Learning technologies punctuated by the proliferation of generative AI models. Considering the speed with which AI is becoming pervasive, having a strong grasp of AI concepts and frameworks is critical especially for aspiring AI product managers without significant technical (e.g., coding) background. This opens up exciting opportunities for non-technical product managers whilst making the field of AI product management more accessible, which is a precursor for innovating and building groundbreaking products that address complex, real-world challenges through leveraging cutting-edge technology. Product managers may have to unlearn things they learned in the past. It requires a new mindset.

Insight: Are Automation and Robotization Changing How We Value Our Careers?

Work, the workforce, and the workplace is subjected to constant disruption primarily as a result of advancements in technology. Weather it is the impact of robotization to manual work or the disruption of knowledge-based work as a result of software-enabled innovation, career values are being redefined to accommodate for the evolving nature of work. This begs many questions, most importantly, the short and long-term implications of such advancements in technology to the concept of work as we ‘used’ to know it and by extension the values we associate with our careers. Using a novel data of resumes from 16 million individuals in the United States, this research study shades light on the existential question of technological disruption to the labor market and impact on career values.

Data Contracts: Data Quality for AI

The following insights are derived from a recent Insights from the Field event featuring Chad Sanderson, covering the topic of Data Contracts for achieving high-quality data for Artificial Intelligence (AI). Overview Chad began this session by demystifying some hyperbolic claims in the world of Artificial Intelligence (AI), including the idea that AI models could replace […]

Using Analytics to Find Value in Education Data

The following insights are derived from a recent Assembly talk featuring Hywel Benbow, regarding applying data analytics to enhance the performance of educational institutions. We presented a few question to Hywel during this talk, and what follows is a summary of his responses. Could you speak to some overarching and generalizable ways educational organizations could […]

Scaling Generative AI in the Enterprise – A Fireside Conversation with Bratin Saha

Since the launch of ChatGPT, GenAI has taken center stage, prompting business leaders to explore its potential for creating value. In a recent stimulating discussion featuring Bratin Saha, Iavor Bojinov, and Edward McFowland III, the conversation delved deep into the radical potential of GenAI and its seismic impact on businesses.

The Impact of Innovation Contests in Federally Qualified Health Centers

The following insights are derived from a recent Assembly talk featuring Olivia Jung, PHD, and Andrea Dorbu, MPH on Innovation Contests in Federally Qualified Health Centers in the United States. In this talk, Andrea and Olivia discussed a research project that they conducted across 54 Federally Qualified Health Centers (FQHCs) in the United States to […]

From Data to AI: Maximizing Organizational Value Through Effective Operating Models

The following insights are derived from a recent Assembly talk featuring Samir Sharma, the CEO of datazuum.  

In this talk, Samir emphasizes the importance of connecting data strategy with business objectives via a detailed discussion of operating models, which are structured frameworks or organizational approaches that govern how an organization manages and utilizes its data analytics and related processes. Samir draws from his expertise in organizational psychology to highlight the challenges organizations face in embedding data and analytics into their core practices and considers the critical role of talent, systems, processes, and upskilling in building a successful operating model.

See table for a summary of the five types of operating models Samir discussed in this talk along with the advantages and challenges that come with adopting each model in a business setting.

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